Dichotomic node network and cognitive trait model

In the search of creating a representation, such as a cognitive trait model, of cognitive traits, such as working memory capacity or inductive reasoning ability, of a learner, it is hard to find a consensus model of the cognitive trait among different perspectives of cognitive science. Dichotomic node network (DNN) is developed to provide a viable solution to this problem. DNN is a network representation of an entity of which the constituents are nodes that is consisted of a pair of dichotomic attributes. Through the contradiction detection mechanism and inclusion resolution mechanism, DNN is able to: (1) represents of an entity contains multiple portrayals/perspectives; (2) select appropriate portrayals for any particular entity is very difficult or impossible; (3) handle nonlinear aggregation of portrayals in which combinations does not render result linearly, and therefore very suitable for cognitive trait model, and is potential for other applications.